Deepseek 4.1 and deepsek dsh after month of use

[u/N3Rumie]

So exacly 26 days ago i made post how bad it was to use deepsek on my reasonix configuration. It showed 1/10th of avilable contex and worked much worse than 4 pro

Since then i moved to dsh and began testing it, fix broken mod for civ, make one of your own and stuff like that. (he played over 60 round game of civ by himself to test the mod which was funny. I had ai playing games at home when i was at work)

Now with the whole ai decompilation trend i decided to utilize deepseek for similliar task. Two weeks, 9 and half bilion tokes later:

1. Deepseek rarely spawns subagents by himself, oftend needs to be nudged to do that but then he begans to utilizing them on regular basis

2. Alwyas around 60% of contex he talks internaly how he should preserve contex and butchers outputs and changes tasks since "contex is low so i should focus on A instead of B"

3. 4.1flash prefers running his own tests and build tools despite having large amount of notes that disprove his theories or tools thst alredy does what he wants.

4. Despite having doctrine of work and readme that asks him to check the notes or write new ones he needs to be prompted after tests to document them even if they didnt

Fully automated decompiling work with deepseek is hard and i would say immposible, needs constant attention to the work he alredy did and is doing to remind him "we alredy tested thst"

I told him to read note of our recent failure

"our change in the code changed mesh to m20 instead of our f24" that was problem in the note

But same note had correction "real problem was our change forced lower graphical settings in game that loaded model we had bound to incomplete family f24"

And despite that he writed 3 theories and probable solution on bassles speculation.

Once model was so dead set on the solution that i ordered it to spawn 4 subagent with varied prompts so they check our notes and come up with they own theories.

Main agent debated them and lost finnaly accepting different approach to the problem, which was arguabbly most productive sessiosn.

Despite its shorcomings, i managed to produce working mods, decompile sucesfully part of the engine and introduce things that were deemed impossible to that engine.

Edit: misspelings and conclusion

[u/ptyblog]

I use OpenCode and it spawns sub gents, I just recently added Opencode Ensemble and is working even better

[u/stujmiller77]

I use deepseek 4.1 flash locally on 4x nivida sparks and it calls sub-agents with no issues. Main harness is Hermes agent, with multiple profiles able to reliably call sub-agents when they need to. I've tested DSH too, also had no issues.

[u/N3Rumie → u/stujmiller77]

It does call subagents But i am not sure if its something on my configurations but he does it really rarely. Only for large parrarel work like scanning, deconpiling and indexing 2 different file types, most of the time even if plan allow for some parrarel work it just does them one after another

[u/stujmiller77 → u/N3Rumie]

So create skills so it knows when you want it to. DSH like all harnesses supports them.

[u/Every_Grass_3504]

The “60% of context” behavior may be coming from the agent harness’s own compaction threshold, not the model’s full context limit; worth checking what the IDE or runner actually sends on each turn. A curated notes index and a firm rule to read relevant notes before testing and document findings afterward may help more than adding more instructions to the prompt. We build TemprHQ, which lets you compare listed context limits and estimate token costs across models.

[u/Random_182f2565]

Thank you for telling us you experience

[u/foo-bar-nlogn-100]

You can ask it to design you memory management but for context blocks that you swap in and out of file system.

You have a multiplier for thr practical context window and when it hits it thay practical context size, it compacts the context window and does some calculation on locality of reference based on the current file set and line number range the currwnt agent or orchestrator cursor is at, to determine what context window to swap in.

Note: I use open code cli qith subagent and have an entire pipeline for agent messaging work items

[u/lompocus]

does anyone have advice for forcing ds4.1 to do tool calls in parallel? it likes spawning agents one at a time which is slow....

[u/Excellent-Ad-9607 → u/lompocus]

maybe you have some plugins for orchestration like aegis? it’ll help if you turn them off. I using DSH, there was no such problem for me for any kind of task. But when I downloaded some plugins, there was. So I decided to go without

[u/xapep → u/lompocus]

The serial spawn is usually two different things stacked, worth separating them.

First, the model: DS4.1 will emit multiple tool calls in one turn if you tell it the calls are independent. It plays it safe and sequences when it suspects dependencies, which is why the keyword observation in this thread matches: it needs an explicit cue like "these subtasks are independent, execute them in parallel in a single turn". If the prompt frames the work as a pipeline (step A then B then C), it will obey that shape.

Second, the harness: even when the model returns parallel tool calls, the client decides whether to run them concurrently. DSH serializes by default unless you configure parallel execution, and plugins can flip that behavior. Check the harness config for a parallel tool execution setting before blaming the model.

Quick test to see which layer is the bottleneck: give it a prompt with three obviously independent calls (read two files, query an API) and inspect the raw response. If all three calls come back in one assistant turn but execute one at a time, it is the harness. If the model emits one call per turn, it is the prompt.

[u/Specific_Yam_4666 → u/lompocus]

Ask the model why first because there might be a reason. Start a fresh agent and get it to look at logs to see. If it no reason, then It’s cheaper just to tell agents what you want.

I don’t use dsh but it’ll have a system prompt that tells the agent the how to use its tools and it will have the commands to call sub agents. Then you maybe find this changes against plugins, so check that

Anyway, the model is gong to be able to tell you about the harness features

[u/Either-Nobody-3962]

hey, i have a question, can you please answer?

Currently i am using claude app on windows desktop and someone said, deepseek latest version can do same, so i installed and i tried to do same thing with it.

even after giving claude chats access, all md files it made...it still struggled for 45mins to get things done.

so my question is...is it worth jumping to deepseek? i know money wise it is almost same $20 but people say we get more access to it, is that true?

[u/N3Rumie → u/Either-Nobody-3962]

Sorry i cant say how deepseek compares to claude, honestly i used 5 dollars worth of claude in this project and he never delivered anything beyond one plan that failed. Then again i used 50 dollars worth of deepsek and he fails constsntly.

[u/Either-Nobody-3962 → u/N3Rumie]

hmm, that answers the question then :)

we need to give some more time for it to improve more....

[u/GioNatro1999]

Thanks for sharing, I am thinking to use DHS for modding and reverse engineering warcraft 3, could you please provide some details about setup? like some tools and skills that you used, or some repos perhaps. It would be very useful for me

[u/N3Rumie → u/GioNatro1999]

i am using ghidra. and those repos:
rehan-remade/universal-modder
bethington/ghidra-mcp
trevaintdead/ai-game-modding-guides
there is also : morluto/rea but i havent tested it since i dont have their licence
i have this as part of the file every session reads:

LAW 1 — A wrong decode is silent. Wrong bytes rarely throw. They produce a value that parses, looks
reasonable, and is consistent with itself. "Do not treat a clean parse as validation."

LAW 2 — Two independent readers beat more reasoning. When a decode is in question, do not think harder;
get a second implementation to read the same bytes and diff the two answers.

LAW 3 — The engine is the only judge of anything you hand it. Offline analysis can never falsify a claim
about what the engine accepts. A hash, an offset, a name you chose: unverified until the engine consumes it.

LAW 4 — Change one thing at a time, and make "nothing happened" informative. A write that does nothing
tells you the name was not recognised; a write that crashes tells you it was — that is progress. Design the
experiment so both outcomes teach you something, and so a crash is survivable and attributable.

LAW 5 — Write down what you believed and why it looked right. The correction is half the value; the
"why it looked right" is the other half, and it is the half that stops the next agent.

LAW 6 — A citation is a decode. "I read the document" and "it appeared in a search result" are different
claims, and they must be labelled differently. A plausible reference — right parties, right year, right case number — can be entirely fabricated and still survive a review, because it looks like an authority.

[u/GioNatro1999 → u/N3Rumie]

Thank you, that would for sure be useful 🙌

[u/AdvancedBar9553]

That's a pretty interesting result considering how much context it seems to lose. What do you think helped most in the end, better notes or using subagents to challenge its assumptions?

[u/N3Rumie → u/AdvancedBar9553]

Better notes are good but you need point him when you see when something resembles already encounreed problem.example from hour ago: I created tools and obsidian vault skills to point him at our tools We are moding frostbite and managed to find way to deliver new assets, now i wanted him to make it reproductible. He had good streak of work, until it got to delivery. Our new asset 1 worked and new asset 2 had null pointer error. So he begun to using decoded assets to dig why until i stoped him and uset vault skill to check first if we encountred that problem.

subagents challenge produced 4 test to run, 3 test ran by agents and great varaiety of angles to work from. I would say this is better approach if you have unlimited tokens since all of them consumed on avarage 15m of tokens

[u/jorgeaah]

Now that you mention subagents. Using Sol as main Llm and deepseek as subagent, is working great.

[u/Glad_Historian9051]

Dis lui simplement de travailler sur son soul.md, et dit lui d'intégrer cette notion dans son fonctionnement. Et va te proposer des modèles de contenu. Tu lui dit go et tu valides. Moi ça la débloqué.

[u/Big_Emergency_8188]

Sounds like you don't have any memory plugin?

[u/imoshudu]

"4.1flash prefers running his own tests and build tools despite having large amount of note"

Sorry but this just means you failed to set up a decent external memory provider. That is a rabbit hole to go into but they're there for reason. My deepseek doesn't repeat work.

[u/Fancy-Passage-1570]

Same, if you don't specify that he can use subagents he will rarely think about it. Does trigger on certain keywords do like "Rework, Refactor, Verify and multiple pass". But for a reverse engineering job or cross info you have to tell him.

And for reverse engineering binaries or network protocols the hallucination rate is insane. despite having a workflow with methodology + llm wiki, deepseek ofter hallucinate functions or binaries. You have to baby sit him, the model has a hard time for long complex horizon tasks that requires fine details